Alan Griffin1, Ian C Kenny2,3, Thomas M Comyns2,3, Mark Lyons2. 1. Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland. alan.griffin@ul.ie. 2. Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland. 3. Health Research Institute, University of Limerick, Limerick, Ireland.
Abstract
BACKGROUND: There has been a recent increase in research examining training load as a method of mitigating injury risk due to its known detrimental effects on player welfare and team performance. The acute:chronic workload ratio (ACWR) takes into account the current training load (acute) and the training load that an athlete has been prepared for (chronic). The ACWR can be calculated using; (1) the rolling average model (RA) and (2) the exponentially weighted moving average model (EWMA). OBJECTIVE: The primary aim of this systematic review was to investigate the literature examining the association between the occurrence of injury and the ACWR and to investigate if sufficient evidence exists to determine the best method of application of the ACWR in team sports. METHODS: Studies were identified through a comprehensive search of the following databases: EMBASE, Medline, SPORTDiscus, SCOPUS, AMED and CINAHL. Extensive data extraction was performed. The methodological quality of the included studies was assessed according to the Newcastle-Ottawa Scale (NOS) for Cohort Studies. RESULTS: A total of 22 articles met the inclusion criteria. The assessment of article quality had an overall median NOS score of 8 (range 5-9). The findings of this review support the association between the ACWR and non-contact injuries and its use as a valuable tool for monitoring training load as part of a larger scale multifaceted monitoring system that includes other proven methods. There is support for both models, but the EWMA is the more suitable measure, in part due to its greater sensitivity. The most appropriate acute and chronic time periods, and training load variables, may be dependent on the specific sport and its structure. CONCLUSIONS: For practitioners, it is the important to understand the intricacies of the ACWR before deciding the best method of calculation. Future research needs to focus on the more sensitive EWMA model, for both sexes, across a larger range of sports and time frames and also combinations with other injury risk factors.
BACKGROUND: There has been a recent increase in research examining training load as a method of mitigating injury risk due to its known detrimental effects on player welfare and team performance. The acute:chronic workload ratio (ACWR) takes into account the current training load (acute) and the training load that an athlete has been prepared for (chronic). The ACWR can be calculated using; (1) the rolling average model (RA) and (2) the exponentially weighted moving average model (EWMA). OBJECTIVE: The primary aim of this systematic review was to investigate the literature examining the association between the occurrence of injury and the ACWR and to investigate if sufficient evidence exists to determine the best method of application of the ACWR in team sports. METHODS: Studies were identified through a comprehensive search of the following databases: EMBASE, Medline, SPORTDiscus, SCOPUS, AMED and CINAHL. Extensive data extraction was performed. The methodological quality of the included studies was assessed according to the Newcastle-Ottawa Scale (NOS) for Cohort Studies. RESULTS: A total of 22 articles met the inclusion criteria. The assessment of article quality had an overall median NOS score of 8 (range 5-9). The findings of this review support the association between the ACWR and non-contact injuries and its use as a valuable tool for monitoring training load as part of a larger scale multifaceted monitoring system that includes other proven methods. There is support for both models, but the EWMA is the more suitable measure, in part due to its greater sensitivity. The most appropriate acute and chronic time periods, and training load variables, may be dependent on the specific sport and its structure. CONCLUSIONS: For practitioners, it is the important to understand the intricacies of the ACWR before deciding the best method of calculation. Future research needs to focus on the more sensitive EWMA model, for both sexes, across a larger range of sports and time frames and also combinations with other injury risk factors.
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